Related papers: Data Processing Engine (DPE): Data Analysis Tool f…

The increasing proliferation of digital and mobile devices equipped with cameras, microphones, GPS, and other privacy invasive components has raised significant concerns for businesses operating in sensitive or policy restricted…

As the particle physics community needs higher and higher precisions in order to test our current model of the subatomic world, larger and larger datasets are necessary. With upgrades scheduled for the detectors of colliding-beam…

The Phase Estimation Algorithm (PEA) is an important quantum algorithm used independently or as a key subroutine in other quantum algorithms. Currently most implementations of the PEA are based on qubits, where the computational units in…

Machine learning assisted modeling of the inter-atomic potential energy surface (PES) is revolutionizing the field of molecular simulation. With the accumulation of high-quality electronic structure data, a model that can be pretrained on…

An open-source, Python-based Temporal Analysis of Products (TAP) reactor simulation and processing program is introduced. TAPsolver utilizes algorithmic differentiation for the calculation of highly accurate derivatives, which are used to…

Edge computing is naturally suited to the applications generated by Internet of Things (IoT) nodes. The IoT applications generally take the form of directed acyclic graphs (DAGs), where vertices represent interdependent functions and edges…

Electroencephalography (EEG) analysis extracts critical information from brain signals, which has provided fundamental support for various applications, including brain-disease diagnosis and brain-computer interface. However, the real-time…

With the rapid development of network protocol, TCP/IP has been widely applied in various OS systems because of its advantages of high-speed network transmission and standardization. Furthermore, TCP/IP has the functions of retransmission…

High parallel framework has been proved to be very suitable for graph processing. There are various work to optimize the implementation in FPGAs, a pipeline parallel device. The key to make use of the parallel performance of FPGAs is to…

Deep learning on an edge device requires energy efficient operation due to ever diminishing power budget. Intentional low quality data during the data acquisition for longer battery life, and natural noise from the low cost sensor degrade…

Transition Edge Sensors (TESs) are amongst the most sensitive cryogenic detectors and can be easily optimized for the detection of massive particles or photons ranging from X-rays all the way down to millimetre radiation. Furthermore, TESs…

The Dark Matter Particle Explorer (DAMPE) is designed as a high energy particle detector for probing cosmic-rays and $\gamma-$rays in a wide energy range. The trajectory of the incident particle is mainly measured by the Silicon-Tungsten…

One of the main purposes of the DArk Matter Particle Explorer (DAMPE) is to measure the cosmic ray nuclei up to several tens of TeV or beyond, whose origin and propagation remains a hot topic in astrophysics. The Plastic Scintillator…

This paper introduces an efficient patch-based computational module, coined Entropy-based Patch Encoder (EPE) module, for resource-constrained semantic segmentation. The EPE module consists of three lightweight fully-convolutional encoders,…

Plastic-scintillator detectors are devices used for the detection of elementary particles. They provide good particle identification with excellent time resolution, whilst being inexpensive due to the affordability of plastic materials.…

Data-driven methods (DDMs), such as deep neural networks, offer a generic approach to integrated data analysis (IDA), integrated diagnostic-to-control (IDC) workflows through data fusion (DF), which includes multi-instrument data fusion…

DAMPE (Dark Matter Particle Explorer) is a satellite-born experiment launched in 2015 in a sun-synchronous orbit at 500 km altitude, and it has been taking data in stable conditions ever since. Its main goals include the spectral…

Tip decomposition is a crucial kernel for mining dense subgraphs in bipartite networks, with applications in spam detection, analysis of affiliation networks etc. It creates a hierarchy of vertex-induced subgraphs with varying densities…

Microparticles ranging from sub-microns to millimeter in size are a common form of matter in magnetic fusion environment, and they are highly mobile due to their small mass. Different forces in addition to gravity can affect their motion…

The planned luminosity increase at the Large Hadron Collider in the coming years has triggered interest in the use of the particles' time of arrival as additional information in specialized detectors to mitigate the impact of pile-up. The…